Search Results (26)

Consensus molecular subtype 4 (CMS4) colorectal cancer (CRC) is associated with an aggressive clinical course and poor survival, yet the biological basis of heterogeneity within this subtype remains incompletely understood. DNA methylation is an epigenetic mechanism involved in transcriptional regulation, cellular differentiation, and colorectal tumorigenesis. Here, we integrated single-cell RNA sequencing (scRNA-seq), bulk data, and promoter DNA methylation data to characterize CMS4-associated cancer cell states and methylation-related features. Using the scAB algorithm, we integrated scRNA-seq with bulk CMS4 data and identified CMS4-related cells distributed across multiple patients. Single-cell analyses of cell–cell communication and transcriptional regulation revealed a CMS4-related cancer cell population characterized by macrophage migration inhibitory factor (MIF)-centered intercellular communication, enhanced caudal type homeobox 1 (CDX1) and Kruppel-like factor 5 (KLF5) regulon activity, and gene modules enriched in differentiation-related pathways. CytoTRACE analysis further stratified CMS4 cancer cells into poorly and well-differentiated states, yielding 802 differentially expressed genes (DEGs). Linking these differentiation-associated DEGs with bulk expression and promoter methylation data identified 218 methylation-associated DEGs showing significant inverse methylation expression correlations, suggesting a link between differentiation-related heterogeneity and promoter methylation. Univariable Cox regression followed by LASSO regression further prioritized eight genes for construction of the methylation and differentiation-related prognostic model (MeDiff-PM). MeDiff-PM consistently stratified overall survival in the TCGA CMS4 cohort and two independent validation cohorts, with cutoff-independent continuous Cox analyses further supporting its prognostic association across cohorts. And MeDiff-PM remained prognostically significant after adjustment for available clinical variables. High MeDiff-PM risk scores were associated with activation of P53, WNT, and ubiquitin-mediated proteolysis pathways and with consistent predicted drug response differences for compounds across three CMS4 cohorts. While individual in silico knockout analysis suggested links between MeDiff-PM genes and metallothionein-related and immune-associated transcriptional responses. Collectively, these findings indicate that methylation-associated differentiation features represent a molecular dimension of intra-CMS4 heterogeneity and provide a biologically informed framework for prognostic stratification within CMS4 CRC. Full article

Background/Objectives: Some individuals present with difficulty understanding speech in noise, tinnitus, or both, despite normal conventional audiometric hearing thresholds. This study evaluated whether acoustic stapedial reflex thresholds (ASRTs) could serve as a clinically useful indicator of auditory complaints not captured by conventional audiometry. Methods: ASRTs for pure tones and broadband noise (BBN) were measured in 146 ears (73 participants) from controls, music students, and symptomatic participants. Bayesian random-intercept linear regression models were used to compare ASRTs among groups, adjusting for age and sex. ASRT difference scores were also used for ROC analysis and to estimate the difference between pure-tone and BBN thresholds (“BBN advantage”). Results: Symptomatic ears showed higher ASRTs than control ears with BBN stimuli, after adjustment for age and sex. Symptomatic ears had a lower AvgDiff posterior mean (reduced BBN advantage) than control ears. ASRTs for music students were directionally consistent with an intermediate pattern, but with wider credible intervals and greater uncertainty. Exploratory ROC analysis showed moderate separation between symptomatic and non-symptomatic ears with AvgDiff; however, symptom status was not independently validated against any diagnostic reference standard. Conclusions: The study suggests that a reduced BBN advantage may be associated with auditory complaints in individuals with normal hearing at conventional audiometric frequencies. However, these findings should be interpreted with caution and not used for specific diagnostic purposes, as the symptomatic group was substantially older and symptom status was not independently validated against any diagnostic reference standard. Full article

Background: The transition to university life is characterized by substantial changes in eating behaviors, sleep–wake organization, and lifestyle patterns. Chrononutrition-related behaviors, including meal timing and caloric distribution across the day, may influence metabolic health independently of dietary quantity, yet prospective evidence in university students remains limited. This study aimed to evaluate BMI trajectories during the first academic year and to identify chrononutrition-related behaviors associated with BMI change and clinically significant weight gain in young adults. Methods: This prospective observational study included 921 university students aged 18–24 years. BMI was assessed at university entry and after one academic year, and BMI change (Diff_BMI) was calculated. Chrononutrition-related variables included meal frequency, identity of the main meal, breakfast habits, and late eating. Multivariable linear and logistic regression models were used to evaluate independent associations between chrononutrition-related behaviors, BMI change, and clinically significant weight gain (Diff_BMI > +1 kg/m²). Results: Mean Diff_BMI was −0.45 ± 1.07 kg/m² (95% CI −0.52 to −0.38; p < 0.001). Overall, 48.2% of participants showed BMI reduction, 38.7% remained weight-stable, and 13.1% experienced BMI increases; clinically significant weight gain occurred in 7.2% of the cohort. In multivariable analysis, having dinner as the main meal (vs. lunch) was independently associated with greater BMI gain (β = +0.22 kg/m²; p = 0.004). Male sex was associated with lower BMI gain and lower odds of clinically significant weight increase. Breakfast skipping showed an inverse association with BMI change, whereas meal frequency and late eating were not independently associated with BMI trajectory after adjustment. Conclusions: The temporal distribution of caloric intake, particularly late eating patterns and shifting the principal meal toward later hours of the day, appears more strongly associated with BMI trajectory during the transition to university life than meal frequency alone. These findings support the relevance of chrononutrition-oriented strategies targeting meal timing and circadian eating behaviors in university students. Full article

Accurate prediction of the long-term MPPT degradation trajectory of perovskite solar cells (PSCs) from short-term measurements can significantly reduce the time required for material characterization. Although conditional diffusion models have recently been introduced for degradation prediction in energy devices, their applicability to PSC-specific maximum power point tracking (MPPT) degradation trajectory forecasting remains uncertain due to the complexity of the underlying dynamics. This study benchmarks three approaches using 2245 devices from a publicly available dataset: NHITS, a hierarchical multilayer perceptron (MLP) with direct multi-horizon regression; Probabilistic NHITS (P-NHITS), which utilizes the same architecture with multi-quantile output; and TimeDiff, a conditional diffusion model with a CSDI backbone, autoregressive initialization, mode conditioning, and classifier-free guidance. The results indicate that PSC degradation under controlled conditions is predominantly single-exponential, with device-specific decay rates identifiable within the first 30 h. Therefore, the forecasting task is most appropriately framed as a regression problem rather than a generative one. NHITS achieves a root mean squared error (RMSE) of 0.738 PCE% compared to TimeDiff’s 0.863 (a 17% increase, p < 10⁻¹⁵), despite TimeDiff incorporating all architectural advantages reported in the literature. P-NHITS matches deterministic accuracy (0.744 PCE%) while providing 77% coverage prediction intervals without sampling, which is closer to the nominal 80% target than TimeDiff’s 63% coverage from 50 DDPM samples. For T90 (the time at which PCE first falls below 90% of its reference value) lifetime prediction restricted to forecast-window crossings, NHITS achieves a mean absolute error (MAE) of 16.2 h, outperforming TimeDiff’s 22.5 h. For smooth, unimodal degradation processes, direct regression with quantile outputs is both sufficient and preferable to conditional diffusion. Model selection should be guided by the underlying physical processes rather than by methodological trends. Full article

Accurate estimation of human joint moments from multimodal sensor signals is essential for lower-limb exoskeleton control. Recent studies have addressed this problem in an end-to-end manner, but remain limited by insufficient long-range temporal modeling, limited training data, and class imbalance. To address these issues, we propose Diff-MomentFormer, a generative diffusion-augmented Transformer framework for end-to-end joint moment estimation from multimodal wearable sensor signals. The framework integrates a classifier-free conditional diffusion model for activity-conditioned synthetic data generation, together with a Transformer-based regression network for modeling long-range temporal dependencies and cross-modal interactions. Through the combination of controllable data augmentation and global temporal modeling, Diff-MomentFormer can learn more robust multimodal representations for accurate and stable joint moment estimation. Extensive experiments on a public lower-limb biomechanics dataset show that the proposed method consistently improves hip and knee joint moment estimation performance across different activity categories, while ablation studies further confirm the effectiveness of the proposed framework. Full article

Cardiometabolic abnormalities, which are common in diabetes patients, can be alleviated through exercise. We examined the specific effects of walking (4–5 METS) on diabetic patients’ cardiac function in a randomized study. Patients with type 2 diabetes (metformin-, insulin-, and diet-controlled; n = 32) were randomized to a 12-week walking intervention (40 min, three times/week; n = 16) or standard care (control group, n = 16). We prospectively compared metabolic, anthropometric, cardiac function and cardiorespiratory fitness parameters between the two groups via linear regression. Compared with that of the control group, the postintervention global strain of the walking group improved significantly (−19.0 (±3.0) vs. −20.9 (±2.6), Diff = −1.92 (CI = −2.61–−1.24), p < 0.001; control: −18.7 (±3.2) vs. −18.9 (±3.6), Diff = −0.19 (CI = −1.00–0.63), p = 0.650), with a pre/post between-group estimated mean difference of ~−1.73 (CI = −2.78–−0.69; p < 0.001). Abdominal circumference (−3 cm (CI = −4.41–−1.59), p < 0.001)), resting heart rate/bpm (−6.50 (CI = −9.69–−3.31, p < 0.001)) and body fat percentage (−2.74 (CI = −4.71–−0.76, p < 0.007)) changed significantly only in the walking group. Spiroergometric data revealed improved oxygen uptake in the walking group vs. the control group: abs_VO2max/L·min⁻¹ (0.19 (0.05–0.33), p < 0.008); rel_VO2max/mL·kg⁻¹·min⁻¹ (2.43 (1.03–3.83), p < 0.001). This first randomized intervention study of supervised walking in patients with type 2 diabetes demonstrated that even moderate-intensity physical activity (such as walking) can improve cardiac function and body composition, reduced waist circumference, and increased oxygen uptake, making it a cost-effective treatment with significant preventive and restorative benefits for cardiac function and body composition in these patients. Full article

The ratio of the nucleated cell counts (ΔTNC) provided by the Sysmex XT-2000iV DIFF and BASO channels has been proven to be useful in differentiating effusions in cats; in particular, a ΔTNC > 2.5 was found to have high accuracy for effusive FIP. The objective of this study was to compare the ΔTNC obtained with the Sysmex XT-2000iV and Sysmex XN-1000V on different types of effusions. Fresh effusions from cats were evaluated with both analyzers. WBC-BASO, WBC-DIFF, and ΔTNC-XT from the Sysmex XT-2000iV and TNC-WNR, TNC-WDF, and ΔTNC-XN from the Sysmex XN-1000V were recorded and compared. Forty-five feline effusions were collected. The results were not significantly different for all parameters evaluated. The Passing and Bablok regression analysis for ΔTNC-XT and ΔTNC-XN revealed a slope of 1.612 (95% CI 1.030 to 2.316) and an intercept of −0.744 (95% CI −1.591 to −0.120); the Bland–Altman difference plot showed a positive bias of 4.382 (p = 0.02). Despite the finding of a positive proportional and constant bias between ΔTNC-XT and ΔTNC-XN, evident especially at high ΔTNC values, samples were classified accordingly between the two analyzers when ΔTNC-XT cut-offs were used, allowing the same accuracy for the identification of suspected and compatible FIP samples. Full article

Background/Objectives: Anxiety and depression are prevalent global health concerns, especially prominent in vulnerable groups such as older adults, individuals with chronic health conditions (e.g., neurodegeneration and cancer), and those from low socioeconomic backgrounds. Digital interventions, including computerized cognitive training (CCT), show promise in addressing emotional dysfunctions in a more accessible and cost-effective manner. The CREATE platform aims to enhance Emotion Regulation (ER) through targeted Working Memory (WM) training, aesthetic engagement, and creativity, while accounting for dopamine activity via spontaneous Eye Blink Rate (sEBR). The purpose of the present study is to evaluate the platform’s feasibility and validity through a single pilot trial. Methods: The study enrolled twenty-seven healthy adults (aged 21–44) who completed standardized self-report questionnaires on sleep quality and ER. They were also enrolled in sEBR recordings and performed a CCT-adapted Corsi block-tapping task and an aesthetic art evaluation. Affective textual narratives and valence/arousal ratings were also collected. Participants were divided into “Good Sleepers” and “Poor Sleepers”. The platform evaluation enrolled a multi-modal pipeline including correlations and regression analysis of intervention metrics, sentiment analysis, and group comparisons. Results: WM task performance correlated positively with global ER and Cognitive Reappraisal scores. Post-training sEBR was significantly associated with ER, and lower sleep efficiency negatively impacted changes in dopamine activity (sEBR Diff). Dopamine activity of “Good Sleepers”, as indicated by sEBR, reached the high levels of the “Poor Sleepers” group after the training, suggesting a dopamine boost caused by the CREATE platform for those with quality sleep. Creativity and emotional expression, as indicated by sentiment analysis, were related to sleep quality. Conclusions: The CREATE platform shows promise in enhancing ER through multi-modal digital engagement, integrating cognitive training, art, and creativity. The findings support the inclusion of sleep and dopamine markers in intervention evaluation. Further studies with larger samples and clinical cohorts are warranted to establish efficacy and generalizability, as the present one was not powered to test the effectiveness of our training platform but was designed to assess its feasibility and validity instead. Full article

Trends in electrical energy efficiency are key factors influencing production costs in food industry plants, as all production equipment relies on electricity. Accurate forecasting is essential for predicting future consumption and enabling effective energy management. This study aims to analyze and forecast trends in electrical energy efficiency in the food industry. Production and electricity consumption data from January 2022 to December 2023 were used to calculate the difference in electrical energy (DIFF) and the cumulative sum of electrical energy differences (CUSUM), which served as the basis for forecasting. The Long Short-Term Memory (LSTM) model, based on the deep learning approach, was employed to simulate the algorithmic patterns of electrical energy data in the food industry. Its forecasting performance was then compared with two alternative models, namely decomposition and logistic regression, using evaluation data from January to December 2024. Model accuracy was assessed using the Mean Absolute Percentage Error (MAPE) criterion. The results revealed that the decomposition model achieved lower MAPE values for both DIFF (14.47%) and CUSUM (24.13%), while the logistic regression model yielded higher MAPE values of 73.70% and 66.85%, respectively. Therefore, the decomposition model was identified as the most suitable method for forecasting electrical energy consumption trends in the food industry, providing higher accuracy and reliability than logistic regression. Forecasting energy consumption trends using the decomposition model can support strategic energy planning to enhance efficiency, reduce costs, and promote the sustainable development of the food industry in the future. Full article

Synthetic aperture radar (SAR), with its all-weather and all-day active imaging capability, has become indispensable for geoscientific analysis and socio-economic applications. Despite advances in deep learning–based object detection, the rapid and accurate detection of small objects in SAR imagery remains a major challenge due to their extremely limited pixel representation, blurred boundaries in dense distributions, and the imbalance of positive–negative samples during training. Recently, vision–language models such as Contrastive Language-Image Pre-Training (CLIP) have attracted widespread research interest for their powerful cross-modal semantic modeling capabilities. Nevertheless, their potential to guide precise localization and detection of small objects in SAR imagery has not yet been fully exploited. To overcome these limitations, we propose the CLIP-Driven Adaptive Tiny Object Detection Diffusion Network (CDATOD-Diff). This framework introduces a CLIP image–text encoding-guided dynamic sampling strategy that leverages cross-modal semantic priors to alleviate the scarcity of effective positive samples. Furthermore, a generative diffusion-based module reformulates the sampling process through iterative denoising, enhancing contextual awareness. To address regression instability, we design a Balanced Corner–IoU (BC-IoU) loss, which decouples corner localization from scale variation and reduces sensitivity to minor positional errors, thereby stabilizing bounding box predictions. Extensive experiments conducted on multiple SAR and optical remote sensing datasets demonstrate that CDATOD-Diff achieves state-of-the-art performance, delivering significant improvements in detection robustness and localization accuracy under challenging small-object scenarios with complex backgrounds and dense distributions. Full article

Background/Objectives: Inflammatory bowel disease (IBD) patients face elevated gastrointestinal (GI) infection risks due to immune dysregulation and gut dysbiosis. While steroids and immunosuppressants are known to increase infection risk, data on biologics and proton pump inhibitors (PPIs) remain limited, particularly for non-Clostridioides difficile (C.diff) infections. Methods: This retrospective cohort study analyzed 9849 hospitalized IBD patients (2013–2023) from the Northwell Inpatient Database. Patients were categorized into four groups: biologics-only, PPIs-only, both, or neither. GI infections were identified via C.diff PCR, GI PCR, and chart review. Multivariate logistic regression adjusted for demographics, BMI, and IBD type. Results: GI infections occurred in 1.75% of patients, with significantly higher odds in those on biologics alone (OR 21.5, 95% CI 11.7–39.4) or with PPIs (OR 16.6, 95% CI 10.2–26.8) versus untreated patients. Non-C.diff infections were strongly associated with biologics (OR 20.7, 95% CI 10.2–41.9). PPIs alone increased slightly the risk of GI infections (OR 1.6, 95% CI 1.1–2.4). Vedolizumab and adalimumab had the highest infection risks among biologics (26.8% and 22.7%, respectively). Bacterial pathogens, such as E. coli and Salmonella, predominated, with no significant difference in causative agents across treatment groups. Conclusions: Biologic therapy greatly increases GI infection risk in IBD patients independent of PPI use. Clinicians should weigh infection risks when prescribing biologics, particularly in high-risk populations. Further studies are needed to assess risks by biologic subtype and the interplay with PPIs. Full article

Background: The role of the periarticular muscles of the knee joint in ensuring body balance is still ambiguous. Therefore, we conducted clinical and biomechanical assessments on 52 older adults (36 women and 16 men, age of 67.58 ± 7.30 years, body weight of 75.10 ± 13.42 kg, and height of 163.92 ± 8.80 cm) to determine the role of the knee muscles in balance maintenance. Methods: The clinical examination included the Dizziness Handicap Inventory (DHI), the Geriatric Depression Scale (GDS), the Performance-Oriented Mobility Assessment (POMA), the Functional Reach Test (FRT), the Falls Efficacy Scale—International (FES-I), and bioimpedance parameters (skeletal muscle mass—SMM—and its derived parameter—Diff SMM). The biomechanical assessment involved parameters that characterize muscle torques of knee joint extensors and flexors in isokinetic and isometric conditions, as well as changes in the centre of pressure (COP) position while standing with eyes open and closed. Results: Based on treatment history and DHI results (>10 points), 26 participants were identified as having balance disorders, while the remaining participants formed the control group. Statistical analysis was performed to determine differences between the groups. The groups significantly differed in terms of the results obtained from the DHI (p < 0.001) and GDS (p = 0.04) questionnaires as well as FES-I (p < 0.001) and POMA (p = 0.002) tests. While SMM (p = 0.012) was similar in the groups, Diff SMM (p = 0.04) significantly differed. The multiple regression analysis confirmed the knee joint extensor parameters’ significant role in predicting the COP path (p = 0.03 and p = 0.04 for two assumed models). Conclusions: The obtained results proved that the muscle torques of knee extensors can be used in the diagnostic process of older patients with balance disorders, indicating possible rehabilitation directions. Full article

Bone fractures are associated with hypoxia, but no longitudinal studies of perfusion measurements in human patients have been reported despite the clinical and research potential. In this longitudinal observational cohort study, the near-infrared spectroscopy (NIRS) device PortaMon was used to assess oxy-(O₂Hb), deoxy-(HHb) and total (tHb) haemoglobin, as well as the differences between O₂Hb and HHb (Hb_Diff) and the tissue saturation index (TSI) at three different depths in the fracture gap. Linear mixed effect models were fitted to analyse time effects. One-way ANOVAs were conducted to compare groups. The time points corresponding to minima were calculated via linear regression. In this study, 11 patients with tibial shaft fractures underwent longitudinal measurements. Additionally, 9 patients with diagnosed tibial shaft nonunion and 23 age-matched controls were measured once. In the longitudinal group, all fractures healed, and decreases in O₂Hb and Hb_Diff (all p < 0.05) were observed, with minima occurring 19–21 days after fracture. O₂Hb values in nonunion patients did not differ from the minima in longitudinally measured union patients, whereas differences in HHb and tHb were significant (all p < 0.05). Previously, the onset of hypoxia has been assumed to be much faster. The characteristic trajectories of the NIRS parameters O₂Hb and Hb_Diff can be used to fulfil the need for a non-invasive method to monitor fracture healing. These results suggest that NIRS could supplement radiographs and clinical impressions in daily clinical practice and may enable earlier diagnosis of nonunion. Full article

To explore the connotation and development level of China’s new quality productivity, this paper constructs an index system based on innovation, greenness, and productivity. This system is used to describe the development level of China’s new quality productivity. Using relevant data from 30 provincial administrative regions in China from 2011 to 2021, the entropy weight-TOPSIS method was employed to measure the index system. The development level of new quality productivity in China and its four major economic regions was analyzed through the three dimensions of the index system. Additionally, this paper examines the impact of new quality productivity on China’s industrial restructuring and integrates environmental regulation to elucidate the interaction mechanisms among these factors. An econometric regression model is further constructed to verify the effect of new quality productivity on industrial structural change and to examine the moderating role of environmental regulation. The results of this study show that there is a regional imbalance in the level of development of new quality production in China, with the level of development of new quality productivity in the eastern region being significantly higher than that in the central, western, and northeastern regions. However, on the whole, the new quality productivity of the four major regions has been in a state of continuous improvement during the period under investigation, and the spatial gap has been constantly decreasing. The benchmark regression coefficients, sys-GMM regression coefficients, and diff-GMM regression coefficients for new quality productivity and industrial rationalization are −0.6228, −0.1121, and −0.0439, respectively, and they are negatively correlated. The regression coefficients of the sys-GMM and diff-GMM of the interaction terms of environmental regulation and new quality productivity are −0.0051 and −0.0045, and there is a negative moderating effect of environmental regulation between new quality productivity and industrial structure rationalization. The benchmark regression coefficient, the sys-GMM regression coefficient, and the diff-GMM regression coefficient of new quality productivity and industrial upgrading are 2.5179, 0.7525, and 0.3572, respectively, and there is a positive correlation between the two. The regression coefficients of sys-GMM and diff-GMM for the interaction terms of environmental regulation and new quality productivity are 0.0380 and −0.0167, and there is a positive moderating effect of environmental regulation between new quality productivity and industrial structure upgrading. Full article

Purpose: Healthcare-associated infections (HAIs) place a significant financial burden on United States hospitals. HAI treatments extend hospital lengths of stay and increase hospital operational costs while significantly reducing hospital profit margins. Given these challenges, the research aim of this study was to explore the association between HAIs and hospital financial performance. A better understanding of this relationship can assist hospital leaders in optimizing the use of scarce financial resources to reduce HAI prevalence. Methods: Data for calendar year 2022 for active short-term acute care hospitals (n = 1454) in the US were analyzed using multiple linear regression analysis. We explored two derived dependent variables, operating expense per staffed bed and operating expense per discharge. The independent variables included four healthcare-associated infection rates: methicillin-resistant Staphylococcus aureus (MRSA) infection rate, Clostridium difficile (C. diff) infection rate, Catheter-Associated Urinary Tract Infection (CAUTI) rate, and Central Line Associated Blood Stream Infections (CLABSI). Appropriate organizational and market-level variables that may independently influence hospital financial performance were included as control variables. Results: The results revealed that C. diff (β: 0.037, p < 0.05) and CAUTI (β: 0.031, p < 0.05) rates were positively associated with an increase in operating expense per staffed bed, while increases in MRSA (β: 0.042, p < 0.001), C. diff (β: 0.062, p < 0.001), and CAUTI rates (β: 0.039, p < 0.001) were correlated with increased operating expenses per discharge. Conclusions: This study demonstrates that specific HAIs may be associated with increased hospital expenses. Proactively targeting these infections through tailored interventions may lead to reduced hospital costs, improved financial performance, and economic stability. Full article